We validate our proposed algorithm on the DRIVE database [1]} for performance evaluation. The DRIVE database is publicly available to execute a comparative study and experimental evaluation of vascular segmentation algorithms. The gold standard segmented images are provided with the database as manually labeled images. The DRIVE database contains 40 color retinal images which include 20 images in training set and 20 images in the test set. All images were captured by Canon CR5 nonmydriatic 3 charge-coupled-device (CCD) cameras at 45o field of view (FOV). Each color retinal image is having a resolution of \(565\times 584\)  pixels with three R, G, and B channels, and each channel is an 8-bit grayscale image. In this paper, we examined our presented algorithm on images from the test set. For test set, two subsets of manually segmented images, i.e., set A and set B, are provided. Set A as the first observer's manual segmented images are considered as gold standard which are utilized as ground truth for performance assessment. The primary objective of choosing DRIVE database is to perform a comparative analysis of the presented work with the state-of-art techniques which have been evaluated on the same database.
